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Comparing Cloudera’s Impala to …

As different systems pop up that try to make ad hoc analysis of big data sets easy and fast, I thought it was time to make a comparasion between Cloudera’s Impala and other projects for ad hoc anlysis...

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4th Swiss Big Data User Group Meeting

The 4th Swiss Big Data User Group Meeting took place on the 26th November 2012 at ETH Zurich. The number of group members has grown over the last months to over 160 people, nearly 80 of them attended...

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Case Study: Retail WiFi Log-file Analysis with Hadoop and Impala, Part 1

This week we were inspired to do some research, driven by an idea: It must be possible to bring the concepts of tracking users in the online world to retail stores. We are not the experts in retail but...

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Case Study: Retail WiFi Log-file Analysis with Hadoop and Impala, Part 2

Following on from Jean-Pierre’s introduction to this experiment in part 1, I will now expand on the technical details of the data ingestion process using Flume. As you can see in figure 2 from the...

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Case Study: Retail WiFi Log-file Analysis with Hadoop and Impala, Part 3

In the previous article we described how to collect WiFi router logs with Flume to store in HDFS. This article will describe how we did the transformation, parsing, filtering and finally loading into...

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Case Study: Retail WiFi Log-file Analysis with Hadoop and Impala, Part 4

In the previous article we explained how to parse, transform and finally load data into Hive’s warehouse. Now it’s time to talk about querying the data. Before we start, here is how a sample of the...

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